Early on in experimenting with local models, I found that hooking them up to Claude Code worked very well, but it was also really slow.

I used mitmproxy (setup assisted by Claude, natch) to capture Claude Code's entire initial system prompt and the whole thing was (I just double-checked) 162k of JSON.

This led me to start experimenting with Pi, OpenCode, and Hermes...

▲ mh- 2 hours ago | parent [-]

This is interesting, because if I start a fresh session of Claude Code right now and run /context, I see the following:

   Opus 4.8 (1M context)
   claude-opus-4-8[1m]
   23k/1m tokens (2%) 

   Estimated usage by category
   System prompt: 3.9k tokens (0.4%)
   System tools: 13.9k tokens (1.4%)
   Custom agents: 235 tokens (0.0%)
   Memory files: 28 tokens (0.0%)
   Skills: 4.9k tokens (0.5%)
   Messages: 8 tokens (0.0%)
   Compact buffer: 3k tokens (0.3%)
   Free space: 974k (97.4%)

4k tokens is 15-20kB. I'd ask you to paste that into a gist, but it might have sensitive data in it, because I suspect what you're seeing is not just the system prompt.

	▲	mft_ an hour ago \| parent [-]
		Apologies, you're right - I used imprecise terminology. The entire initial JSON structure that was sent from Claude Claude to the LLM at the start of a session was 162k. This included the system prompt together with a list of tools (some with very extensive explanations), MCP server details, etc. I was simply supporting the article's data - their reported 33k tokens is probably roughly 150-165k.